code: def make_hifigan_generator_args(**kwargs):
      defaults = dict(
          in_channels=5,
          out_channels=1,
          channels=32,
          kernel_size=7,
          upsample_scales=(2, 2),
          upsample_kernel_sizes=(4, 4),
          resblock_kernel_sizes=(3, 7),
          resblock_dilations=[(1, 3), (1, 3)],
          use_additional_convs=True,
          bias=True,
          nonlinear_activation="LeakyReLU",
          nonlinear_activation_params={"negative_slope": 0.1},
          use_weight_norm=True,
      )
      defaults.update(kwargs)
      return defaults
  
file_path: espnet/test/espnet2/gan_tts/hifigan/test_hifigan.py
imports: import numpy
  import pytest
  import torch
  from espnet2.gan_tts.hifigan import HiFiGANGenerator, HiFiGANMultiScaleMultiPeriodDiscriminator
  from espnet2.gan_tts.hifigan.loss import DiscriminatorAdversarialLoss, FeatureMatchLoss, GeneratorAdversarialLoss, MelSpectrogramLoss
label_desc: Use image node_id 1 for calling a global function with example usage: make_hifigan_generator_args() and returns: defaults